1. Field of the Invention
The present invention relates to an image signal processor used in facsimiles and scanners.
2. Description of the Prior Art
In conventional apparatuses of this kind, the objects to be processed are primarily characters and the size of a dot in a recording system is set slightly larger than the size of a corresponding theoretical picture element or pixel to reproduce smooth characters in continuous lines.
FIG. 1 shows the outline configuration of the conventional image signal processor. In the figure, reference numeral 1 represents a preprocessor which receives image information, in a multiple level, on a text image divided into component pixels by a scanner and which performs preprocessing on the image information received. Denoted 2 is an adder that adds up the image signal fed from the input terminal 1 and an output from an error filter described later. A threshold generator 3 produces a threshold value used in binarizing the output of the adder 2, i.e., transforming it into a binary signal. A comparator 4 converts the output of the adder 2 into a binary signal according to the threshold value generated by the threshold generator 3. The binary signal of the comparator 4 is sent out from an output terminal 5. A subtractor 6 subtracts the output of the comparator 4 from the output of the adder 2. An error data memory 7 stores the output of the subtractor d as error data. An error filter 8 assigns weight to each of the error data for the binarized signals of pixels adjoining the pixel of interest and sums up the weighted error data.
The preprocessor 1 consists of a Laplacean space filter and corrects the input image signal to make the image sharp.
FIG. 2 shows the outline configuration of the preprocessor 1 in the conventional image signal processor. FIG. 3 shows a matrix indicating the coefficients of the filter.
In FIG. 2, reference numerals 11, 12 indicate one-line buffers that store image information of one line in the main scan direction. Designated 14, 15, 16 are latch circuits that output image information on pixels p, d, c in the matrix of FIG. 3 out of the image information stored in the one-line buffers 11, 12. Denoted 13 is a latch circuit that generates image information of the pixel a in the matrix. Adders 17, 18, 19 add information of pixels adjoining the pixel of interest in the matrix. A multiplier 20 multiplies with a negative coefficient the result of addition of the surrounding pixels obtained from the three adders. A multiplier 21 multiplies the pixel of interest, i.e., the center pixel in the matrix, with a coefficient which is so adjusted that the overall coefficient of the filter is unity. An adder 22 adds up the results from the multipliers 20, 21 to produce the sum of the pixel of interest and the surrounding pixels, both multiplied by their assigned filter coefficients.
The space filter, as shown in FIG. 3, has a negative filter coefficient assigned for pixels adjoining the pixel of interest in the main and sub scan directions and a zero or negative filter coefficient assigned for pixels adjoining the pixel of interest in diagonal directions.
In such a conventional image signal processor, a scanner not shown feeds image information of text as multi-level signals of pixels to the input terminal. The input data is processed by the filter in the preprocessor 1 of FIG. 2. In this filter, the multi-level signals output from the latches 13, 14, 15, 16 are taken to be a, p, d, c. Of the multi-level signals at the output of the one-line buffer 11, a multi-level signal of a pixel adjoining the center pixel P one the side opposite to the scan direction is taken as b in FIG. 3. The pixel of interest P and the surrounding pixels a, b, c, d are multiplied by filter coefficients to amplify the high-frequency components in the main and sub scan directions to correct the fuzziness and sharpens the image.
The image signal subjected to the above preprocessing is entered into the adder 2. The adder 2 adds the output of the error filter 8 to the image signal thus entered. Then, the comparator 4 binarizes the output of the adder 2 according to the threshold value supplied by the threshold generator 3. The binary signal produced by the comparator 4 is fed to the output terminal 5. The subtractor 6 subtracts the output of the comparator 4 from the output of the adder 2 and stores the result as error data in the error data memory 7. The error filter 8 assigns weight of one-fourth to each of the error data (Error(a) to Error(d)) for the binarized signals of surrounding pixels a-d stored in the error data memory 7, and then sums up the weighted error data (Error(a) to Error(d)). The output of the error filter is added to the input image signal by the adder 2, as described earlier.
In this way, the error between the input image signal and the output image signal, which is the input image signal binarized, is scattered over the surrounding pixels to realize a halftone image reproduction with improved tone fidelity and increased resolution.
The above conventional image signal processor, however, has a drawback. When a photographic image with a screen of 133-150 lines arranged at a common screen angle of 45.degree. is read in at the resolution of 4 line-pairs/mm and processed by the filter to sharpen the image, the image formed of multi-level signals from the filter has a conspicuous moire.
This is caused by the existence of a frequency component (133 lines: about 3.8 line-pairs/mm; 150 line: about 4.2 line-pairs/mm) on the screen image near a sampling frequency (4 line-pairs/mm).
FIG. 4 shows the phase relationship between the sampling frequency used in reading or scanning and the screen image. Nine pixels enclosed in a thick box in the figure correspond to the pixels a-h, P in the spatial filter shown in FIG. 10.
At positions on the image formed of multi-level signals--which are entered, one pixel at a time, into the space filter--where the phase of the sampling frequency agrees with that of the screen image, as shown in FIG. 4(a), the image signal alternates to the extreme levels from one pixel to another. At positions where the phases do not coincide, as shown in FIG. 4(b), the image signal assumes an intermediate level according to the pattern of the screen. When the image signals supplied in these multiple levels are processed by the conventional Laplacean spatial filter, they are amplified, emphasizing the distinction between black and white at locations where the sampling phase and the screen image phase agrees as shown in FIG. 4(a).
At locations on the screen image where the phases do not agree as shown in FIG. 4(b), the nine pixels in the matrix of FIG. 3 produce less distinction between black and white, resulting in a halftone. The matching and mismatching between the sampling phase and the screen image phase result in an emphasized tone difference between the corresponding two areas, causing a marked moire in the filtered image.
In the conventional Laplacean filter the alternating pixel image signal is emphasized by the spatial frequency characteristic of the filter, which is shown in FIG. 5. FIG. 5 shows the amplitude characteristic of the spatial filter over a two-dimensional plane extending from the pixel of interest in the main and sub scan directions. As seen from the relationship, shown in FIG. 4, between the sampling frequency and the number of pixels, FIG. 5 illustrates the spatial frequency-versus-amplitude characteristic, which is obtained from the calculation of matrix made up of a pixel of interest and adjacent pixels. As shown in FIG. 5, the conventional Laplacean filter has a characteristic of amplifying high frequency components in the main and sub scan directions and at the same time amplifying to a greater extent high frequency components in diagonal directions. Hence, the pixel image signals most affected by this filter are the ones whose power spectra extend in the diagonal or 45.degree. direction as in the case of FIG. 4(a), where the sampling frequency matches the frequency component of the screen. This produces a conspicuous moire.
The moire may be removed by taking an arithmetical mean of two adjacent pixels lined in the main scan direction to convert the pixel image signals into an average level during the preprocessing performed prior to the conventional Laplacean filter processing. The arithmetic mean operation, however, makes it impossible to provide sharp pixel images nor reproduce alternating line image such as a resolution pattern.
Further, in the conventional image signal processor, the operation of the circuits after the preprocessor 1 requires that the sum of the densities of multi-level image signals (.SIGMA.fmn) should equal the sum of the densities of the binarized signals (.SIGMA.gmn).
FIG. 6 shows the total of densities of the input image signals and that of the output image signals. FIG. 6(a) represents the input image signals that are received in the multiple levels. Let us assume that the black/white density in this area is 50%. FIG. 6(b) shows the binarized signals, which represent the theoretical output corresponding to the input image signals of FIG. 6(a). The total of the densities of the output image signals is 50%. FIG. 6(c) shows the result of output actually produced by the recording system based on the binarized signals of FIG. 6(b). The sum of the densities of the output image signals is 40%.
In this way, the dot size in the recording system that records a halftone image may become larger than a theoretical dot size (this phenomenon is referred to as thickening for convenience) or smaller (thinning). Such phenomena give rise to a problem of degraded tone fidelity in the image reproduction, including a reduced number of gradation levels that can be reproduced and a degraded tone continuity.
To solve this problem, it has been conceived to add to the apparatus a gamma convertor that performs density conversion to make the input image either darker or lighter before the image processing is carried out.
The apparatus with the additional gamma convertor, however, has another problem that the number of tone levels of the image signals output from the gamma convertor becomes smaller than that of the input image signals, making it impossible to fully compensate for the degraded tone fidelity in the reproduction of a halftone image. Although this problem can be solved by increasing the number of tone levels in the input image signal supplied to the gamma convertor (i.e., increasing the number of bits), an increase in the number of bits in the input image signal requires increasing the number of bits in the image signal processing unit arranged before the gamma convertor, giving rise to another problem of an increased volume of processing. There is still another problem. When the tone level of the input image signal is monotonously increased, the tone level of the output image signal also monotonously increases in the case of a theoretical dot. However, if the dot prints thicker or thinner than required, the tone level of the output image signal does not increase monotonously.
FIG. 7 shows the sums of the output image signal densities for different printing patterns. FIG. 7(a) shows the condition that is identical to FIG. 6(c) and its total density is 40%. It is seen from FIGS. 6(b) and 6(c) that the theoretical density total of FIG. 7(a) is 50%.
FIG. 7(b) shows another print pattern whose theoretical density total is also 50%. The real density, however, is 45% because of the difference in the printing pattern. This is the result of offset or mutual interference between the thickened or thinned adjacent recording dots.
This indicates that an increase in the tone level of the input image signal does not necessarily result in a monotonous increase in the tone level of the output image signal. Thus, fine correction by the gamma conversion is difficult and does not produce a satisfactory solution.